SKILLEMALL.ai
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AC evm-wallet-skill

Self-sovereign EVM wallet for AI agents. Use when the user wants to create a crypto wallet, check balances, send ETH or ERC20 tokens, swap tokens, or interact with smart contracts. Supports Base, Ethereum, Polygon, Arbitrum, and Optimism. Private keys stored locally — no cloud custody, no API keys required.

sundial-org/awesome-openclaw-skills Agent Skills author: sundial-org 1 file body ≈ 1 168 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Self-sovereign EVM wallet for AI agents.

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationAI and agentsSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
95
Quality 40%
84
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Secrets in code secret-high-entropy-token SKILL.md:62
      High-entropy token-like string (may be an id, hash or a credential)
      node src/balance.js base 0x83…913 --json
    • low Secrets in code secret-high-entropy-token SKILL.md:123
      High-entropy token-like string (may be an id, hash or a credential)
      0x83…913 \
    • low Secrets in code secret-high-entropy-token SKILL.md:128
      High-entropy token-like string (may be an id, hash or a credential)
      0x83…913 \
    • low Secrets in code secret-high-entropy-token SKILL.md:158
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - **USDC:** `0x83…913`
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:162
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - **USDC:** `0xA0…8d0`
      quoted

    Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 59/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 22 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1168 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 308: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 22 items
    • +4Has examples (10 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.